Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Abstract— For the past decade or so, evolutionary multiobjective optimization (EMO) methodologies have earned wide popularity for solving complex practical optimization problems,...
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
In this paper, Parallel Evolutionary Algorithms for integer weight neural network training are presented. To this end, each processor is assigned a subpopulation of potential solut...